1. Field of the Invention
The present invention relates to a method and an apparatus for measuring an autonomic-nervous index and an apparatus for detecting biological information.
2. Description of the Related Art
Generally, a polysomnogram for examination is used in medical institutions as a biological information monitoring apparatus that monitors biological information while a target person is in sleep. Apparatuses such as the polysomnogram are capable of monitoring various pieces of biological information such as electroencephalograms, electro-oculogram, and myogram, and determining a change in sleep state such as a rapid-eye-movement sleep (REM sleep) and a non-REM sleep based on the biological information monitored, and furthermore is capable of examining for disease during sleeping such as insomnia and apnea syndrome. However, because such apparatus is large in size, generally, it is used only in specialized institutions.
An apparatus for monitoring a sleep state or a health condition easily at home is developed. For example, JP-A 2002-291710 (KOKAI) and JP-A H07-143972 (KOKAI) disclose technologies in which a heartbeat interval of a heart rate that is an autonomic-nervous activity during sleeping is assumed as a pulse interval of a pulse wave, and a sleep state is determined according to an autonomic-nervous index obtained based on a variation of the pulse interval.
Because the pulse wave, which is a change in blood flow in a blood vessels of a palm, changes in synchronization with a heart rate, the heartbeat interval of the heart rate can be obtained based on the pulse interval of the pulse wave. In the methods disclosed in JP-A 2002-291710 (KOKAI) and JP-A H07-143972 (KOKAI), a series of pulse-interval data, which are monitored during sleeping with a portable biosensor such as a wristwatch type biosensor, are converted into a frequency spectrum distribution. Autonomic-nervous indexes are calculated from the power spectrums of a low-frequency band (LF: a band ranging from around 0.05 Hz to 0.15 Hz) and a high-frequency band (HF: a band ranging from around 0.15 Hz to 0.4 Hz) obtained from the pulse-interval data converted into the frequency spectrum distribution. Then, the sleep state is determined from the autonomic-nervous indexes obtained.
In a general autonomic-nervous analysis method, after the sensor stores raw data of the pulse wave, the raw data stored in the sensor is transferred to a Personal Computer (PC) for analysis, or the raw data sampled by the sensor is transferred to the PC in real time. Then, a pulse-interval detection and an autonomic-nervous analysis are performed on the raw data by an analysis software in the PC. In such a method, a sensor with higher performance is needed to ensure memory for storing the data in the sensor and ensure a communication capacity and a communication speed.
However, generally, a sensor with higher performance is large in size. Thus, using the sensor with higher performance is against the demand of improving a wearability of the sensor by downsizing the sensor. To solve this problem, the data, which is stored in the sensor or transferred to the PC, is compressed to reduce a necessary memory capacity and a communication load. Because only the pulse intervals are needed for monitoring the autonomic-nervous indexes and the sleep state, the data amount can be compressed by storing or transferring only the pulse-interval data, which has smaller capacity, through a pulse interval detecting process in the sensor.
Generally, a sensor that detects such biological information continues monitoring continuously during sleeping, and a monitoring accuracy is sometimes deteriorated due to a posture change of a target person during monitoring, a change in wearing state of the sensor with the posture change, and a temperature change. If raw data of the pulse wave is obtained, the deterioration of the monitoring accuracy is evaluated by analyzing the waveform characteristics.
However, in the method using the pulse-interval data, it is difficult to evaluate the monitoring accuracy, i.e., whether the pulse-interval data is correct. As described above, if raw data of the pulse wave is obtained, the deterioration of accuracy can be evaluated. However, because the advantage of the method of using the pulse-interval data is to utilize not the raw data but the compressed data, the raw data is normally not obtained.